Llama-3.2-3B vs Mistral 7B vs Qwen-VL Plus
Qwen-VL Plus comes out ahead, 57 to 49 and 47 on our weighted score, though Llama-3.2-3B is 2× cheaper per token.
MetaLlama-3.2-3B
49/100- ECI—
- Price$0.10 / $0.335
- Context131K
Mistral AIMistral 7B
47/100- ECI—
- Price$0.25 / $0.25
- Context8K
- Our pick
Alibaba (Qwen)Qwen-VL Plus
57/100- ECI—
- Price$0.21 / $0.63
- Context131K
Qwen-VL Plus is our pick
Qwen-VL Plus is the better all-round choice, scoring 57/100 against Llama-3.2-3B (49) and Mistral 7B (47). It leads on inputs & features. Llama-3.2-3B wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceLlama-3.2-3BLlama-3.2-3B $0.159 · Mistral 7B $0.25 · Qwen-VL Plus $0.315 per 1M tokens (3:1 blend)
- Longest contextLlama-3.2-3B and Qwen-VL PlusLlama-3.2-3B 131,072 · Qwen-VL Plus 131,072 · Mistral 7B 8,000 tokens
- Widest inputsQwen-VL PlusLlama-3.2-3B: Text · Mistral 7B: Text · Qwen-VL Plus: Text, Images
- Self-hostingLlama-3.2-3B and Mistral 7BPublishes downloadable weights (Llama 3.2 Community License)
| Measure | Weight | Llama-3.2-3B | Mistral 7B | Qwen-VL Plus |
|---|---|---|---|---|
| Price | 50% | 88 | 78 | 74 |
| Inputs & features | 30% | 0 | 25 | 50 |
| Context window | 20% | 24 | 0 | 24 |
| Overall | 100% | 49/100 | 47/100 | 57/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Llama-3.2-3BMeta | Mistral 7BMistral AI | Qwen-VL PlusAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 (best) | $0.25 | $0.21 |
| Output | $0.335 | $0.25 (best) | $0.63 |
| Cached input | — | — | — |
| Blended (3:1) | $0.159 (best) | $0.25 | $0.315 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 3 providers | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens (best) | 8,000 tokens | 131,072 tokens (best) |
| Max output | 8,192 tokens (best) | 8,000 tokens | 8,192 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | No | No |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenLlama 3.2 Community License | Open | Proprietary |
| API model ID | — | open-mistral-7b | qwen-vl-plus |
| API providers | 3 (best) | 1 | 2 |
| Released | Sep 25, 2024 | Sep 27, 2023 | Jan 25, 2024 |
| Knowledge cutoff | Dec 2023 | Dec 2023 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Llama-3.2-3B$1.67
- Mistral 7B$3.00
- Qwen-VL Plus$3.36
Which should you choose?
Which is better: Llama-3.2-3B, Mistral 7B or Qwen-VL Plus?
Qwen-VL Plus is the better all-round choice, scoring 57/100 against Llama-3.2-3B (49) and Mistral 7B (47). It leads on inputs & features. Llama-3.2-3B wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Llama-3.2-3B, Mistral 7B or Qwen-VL Plus?
Llama-3.2-3B is cheaper at $0.10 input / $0.335 output per million tokens (median across 3 API providers). Mistral 7B costs $0.25 input / $0.25 output per million tokens (official Mistral API price); Qwen-VL Plus costs $0.21 input / $0.63 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.159 per million tokens for Llama-3.2-3B versus $0.25 for Mistral 7B (1.6× as much) and $0.315 for Qwen-VL Plus (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Llama-3.2-3B has not been scored yet, Mistral 7B has not been scored yet and Qwen-VL Plus has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Llama-3.2-3B, Mistral 7B and Qwen-VL Plus yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Llama-3.2-3B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Llama-3.2-3B and Qwen-VL Plus have the largest context windows (131,072 and 131,072 tokens), against 8,000 for Mistral 7B. Maximum output per response: Llama-3.2-3B up to 8,192, Mistral 7B up to 8,000, Qwen-VL Plus up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Llama-3.2-3B accepts text; Mistral 7B accepts text; Qwen-VL Plus accepts text and images. Qwen-VL Plus handles the widest range of inputs.
Are any of these open source?
Llama-3.2-3B and Mistral 7B publishes its weights (Llama 3.2 Community License) and can be self-hosted; Qwen-VL Plus is proprietary.
Which is newer?
Llama-3.2-3B is the newest, released Sep 25, 2024. Qwen-VL Plus came out Jan 25, 2024; Mistral 7B came out Sep 27, 2023. Knowledge cutoff: Llama-3.2-3B Dec 2023, Mistral 7B Dec 2023, Qwen-VL Plus Apr 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
